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Dataset Card for QA Bias Detection Dataset

Summary

  • Description: This dataset is designed for the task of bias detection in text, particularly focusing on dimensions of ageism and sentiment analysis. It contains question-answer pairs that assess potential biases in statements.
  • Purpose: To facilitate research and development in the areas of bias detection, natural language understanding, and sentiment analysis.
  • Supported Tasks: Bias detection, sentiment analysis, natural language understanding, question answering.
  • Languages: English

Composition

  • Size of Dataset: 3,900 rows.
  • Column Names: ['text', 'dimension', 'aspect', 'biased_words', 'sentiment', 'aggregate_label', 'Bias Type', 'Question', 'Answer', one column for indexing].
  • Data Format: Each record contains a text statement, its associated dimensions and aspects of bias, biased words identified, sentiment, aggregate label for bias, bias type, and a QA pair for bias detection.

Source Data

  • Initial Data Collection and Normalization: curated

Annotations

  • Annotation process: Annotations include bias type, sentiment, and question-answer pairs evaluating the presence and type of bias in the text.
  • Who are the annotators?: Human annotation.

Personal and Sensitive Information

  • Considerations: The dataset contains text that may include sensitive topics related to bias and sentiment.

Considerations for Using the Data

  • Social Impact of Dataset: The dataset could be valuable for developing systems that detect and mitigate bias in textual data.
  • Other Known Limitations: The dataset's effectiveness is limited to the scope of its annotations and the quality of its text sources.